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      • Department of Electrical and Electronics Engineering
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      Man-made object classification in SAR images using 2-D cepstrum

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      Author
      Eryildirim, A.
      Çetin, A. Enis
      Date
      2009-05
      Source Title
      IEEE National Radar Conference - Proceedings
      Publisher
      IEEE
      Pages
      [1] - [4]
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      In this paper, a novel descriptive feature parameter extraction method from Synthetic Aperture Radar (SAR) images is proposed. The new method is based on the two-dimensional (2-D) real cepstrum. This novel 2-D cepstrum method is compared with principal component analysis (PCA) method by testing over the MSTAR image database. The extracted features are classified using Support Vector Machine (SVM). We demonstrate that discrimination of natural background (clutter) and man-made objects (metal objects) in SAR imagery is possible using the 2-D cepstrum feature parameters. In addition, the computational cost of the cepstrum method is lower than the PCA method. Experimental results are presented. ©2009 IEEE.
      Keywords
      Cepstrum
      Cepstrum method
      Computational costs
      Feature parameters
      Image database
      Man made objects
      Natural backgrounds
      PCA method
      SAR imagery
      SAR Images
      Synthetic aperture radar images
      Feature extraction
      Image retrieval
      Imaging systems
      Metal recovery
      Object recognition
      Parameter extraction
      Principal component analysis
      Smelting
      Support vector machines
      Synthetic apertures
      Synthetic aperture radar
      Permalink
      http://hdl.handle.net/11693/26737
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/RADAR.2009.4976990
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      • Department of Electrical and Electronics Engineering 3524
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